Analysis of thrust force in drilling B4C-reinforced aluminium alloy using genetic learning algorithm
Yükleniyor...
Tarih
2014
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper presents an analysis for the prediction of thrust force in drilling of aluminium-based composites, reinforced with boron-carbide B4C produced with the powder-metallurgy (PM) technique. The formulation was derived on experimental bases. The experiments were conducted with various cutting tools and parameters on conditions of dry machining in a computer numerical control (CNC) vertical machining centre. The thrust forces were obtained by measuring the forces between the drill bit and the work pieces during the experiments. In the experiments, particle fraction, feed rate, spindle speed and drill bit type were used as input parameters, and thrust force was the output data for the gene expression programming (GEP) software. Customizing for formulation in order to describe the problem was generated by GEP, and it was analysed from different perspectives and verified the reliability of equation.
Açıklama
Anahtar Kelimeler
Gene Expression Programming, Composite, Drilling, Thrust Force
Kaynak
İnternational Journal of Advanced Manufacturing Technology
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
75
Sayı
01.Apr
